Hyperopt: TypeError: 'generator' object is not subscriptable

[dniku]

from hyperopt import fmin, tpe, hp
best = fmin(fn=lambda x: x ** 2,
    space=hp.uniform('x', -10, 10),
    algo=tpe.suggest,
    max_evals=100)
print(best)

results in

TypeError                                 Traceback (most recent call last)
<ipython-input-1-d4c67c96f9c0> in <module>()
      3     space=hp.uniform('x', -10, 10),
      4     algo=tpe.suggest,
----> 5     max_evals=100)
      6 print(best)

~/.local/lib/python3.6/site-packages/hyperopt/fmin.py in fmin(fn, space, algo, max_evals, trials, rstate, allow_trials_fmin, pass_expr_memo_ctrl, catch_eval_exceptions, verbose, return_argmin)
    312 
    313     domain = base.Domain(fn, space,
--> 314                          pass_expr_memo_ctrl=pass_expr_memo_ctrl)
    315 
    316     rval = FMinIter(algo, domain, trials, max_evals=max_evals,

~/.local/lib/python3.6/site-packages/hyperopt/base.py in __init__(self, fn, expr, workdir, pass_expr_memo_ctrl, name, loss_target)
    784         before = pyll.dfs(self.expr)
    785         # -- raises exception if expr contains cycles
--> 786         pyll.toposort(self.expr)
    787         vh = self.vh = VectorizeHelper(self.expr, self.s_new_ids)
    788         # -- raises exception if v_expr contains cycles

~/.local/lib/python3.6/site-packages/hyperopt/pyll/base.py in toposort(expr)
    713         G.add_edges_from([(n_in, node) for n_in in node.inputs()])
    714     order = nx.topological_sort(G)
--> 715     assert order[-1] == expr
    716     return order
    717 

TypeError: 'generator' object is not subscriptable

This is hyperopt-0.1 freshly installed via pip install.

$ python --version
Python 3.6.4

[dniku]

Btw, commenting out that assert seemingly fixes the issue.

[bheinzerling]

short answer: install from source, this is fixed in master (the hyperopt version on pip is pretty old)

slightly longer answer: a few years ago, nx.topological_sort was changed to return a generator instead of a list, so that assert will fail because it tries to index into a generator, but there is no problem if the subsequent code just iterates over the generator.

[hmehta92]

you can use pip install --upgrade git+git://github.com/hyperopt/hyperopt.git to upgrade hyperopt